Conducting Randomization in Clinical Trials

Randomization is a crucial step that ensures unbiased and fair allocation of participants into different treatment groups in a clinical trial. Clinicians and researchers often resort to online tools, paid tools, and specialized biostatisticians for undertaking randomization. While these may be required for some special cases of randomization, the majority of common aspects can be undertaken by the researchers themselves. In this chapter, we outline the methodology to undertake the most common forms of randomization, namely simple randomization, stratified randomization, block randomization, adaptive randomization, cluster randomization, and minimization. We state the requirements that need to be satisfied beforehand and also demonstrate how to generate and save the sequence. Saving the sequence is a very important step that ensures replicability for audit purposes in the future. Additionally, R, since it is command-line based, helps store the programming codes that were used for the generation of randomization, a feature that may not be available with some online tools. In addition to this, we have added graphical representations to visualize the randomization to ensure that what has been generated is correct. As with all the chapters of this book, each one is supplemented with relevant practical case scenarios, enabling researchers to easily understand and adopt the same in their respective research.